Machine learning (ML) is the study of computer algorithms that improve automatically through experience. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or infeasible to develop conventional algorithms to perform the needed tasks. Machine learning is closely related to computational statistics, which focuses on making predictions using computers.

The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. Data mining is a related field of study, focusing on exploratory data analysis through unsupervised learning.

A key machine learning benefit concerns this technology’s ability to review large volumes of data and identify patterns and trends that might not be apparent to a human. For instance, a machine learning program may successfully pinpoint a causal relationship between two events. This makes the technology highly effective at data mining, particularly on a continual, ongoing basis, as would be required for an algorithm. The ability to quickly and accurately identify trends or patterns is one of the key advantages of machine learning.